by Kathleen Romanik, Kathleen Romanik, Jeffrey Scott Vitter, Jeffrey Scott Vitter
ftp://ftp.cs.duke.edu/pub/dist/techreport/1994/1994-28.ps.Z
Add To MetaCart
Abstract:
Abstract: We examine the complexity of testing different program constructs. We do this by defining a measure of testing complexity known as VCP-dimension, which is similar to the Vapnik-Chervonenkis dimension, and applying it to classes of programs, where all programs in a class share the same syntactic structure. VCP-dimension gives bounds on the number of test points needed to determine that a program is approximately correct, so by studying it for a class of programs we gain insight into the difficulty of testing the program construct represented by the class. We investigate the VCP-dimension of straight line code, if-thenelse statements, and for loops. We also compare the VCP-dimension of nested and sequential if-then-else statements as well as that of two types of for loops with embedded if-then-else statements. Finally, we perform an empirical study to estimate the expected complexity of straight line code. 1
Citations
|
654
|
On the uniform convergence of relative frequencies of events to their probabilities. Theory Probab
– Vapnik, Červonekis
- 1971
|
|
536
|
Learnability and the Vapnik-Chervonenkis Dimension
– Blumer, Ehrenfeucht, et al.
- 1989
|
|
491
|
A Complexity Measure
– McCabe
- 1976
|
|
332
|
Convergence of Stochastic Processes
– Pollard
- 1984
|
|
322
|
Decision theoretic generalization of the PAC model for neural net and other learning applications
– Haussler
- 1992
|
|
259
|
Designing programs that check their work
– Blum, Khanna
- 1995
|
|
233
|
Self-testing/correcting with applications to numerical problems
– Blum, Luby, et al.
- 1993
|
|
148
|
Toward a Theory of Test Data Selection
– Goodenough, Gerhart
- 1975
|
|
125
|
An evaluation of random testing
– Duran, Ntafos
- 1984
|
|
103
|
Computer Algorithms: Introduction to design and analysis, 3 rd Ed
– Baase, Gelder
- 2000
|
|
94
|
Bounding the Vapnik-Chervonenkis dimension of concept classes parameterized by real numbers
– Goldberg, Jerrum
- 1995
|
|
94
|
Evaluating software complexity measure
– Weyuker
- 1988
|
|
62
|
Comparing the Effectiveness of Software Testing Strategies
– Basili, Selby
- 1987
|
|
46
|
Finiteness results for sigmoidal neural networks
– Macintyre, Sontag
- 1993
|
|
29
|
Mutation analysis: ideas, examples, problems and prospects
– Budd
- 1981
|
|
25
|
Theoretical comparisons of testing methods
– Hamlet
- 1989
|
|
21
|
A measure of control flow complexity in program TEXT
– Woodward, Hennel, et al.
- 1979
|
|
13
|
Rates of uniform almost-sure convergence for empirical processes indexed by unbounded classes of functions
– Pollard
- 1986
|
|
11
|
Software testing and evaluation
– DeMillo, McCracken, et al.
- 1987
|
|
8
|
nets and simplex range queries, Discrete and Computational Geometry 2
– Haussler, Welzl
- 1987
|
|
7
|
Automatic Construction of Complete Sample System for Program Testing
– Barzdin, Bicevskis, et al.
- 1977
|
|
7
|
On the Number of Additions to Compute Specific Polynomials
– Borodin, Cook
- 1976
|
|
7
|
Tutorial: Software Testing and Validation Techniques
– Miller, Howden
- 1981
|
|
5
|
A Formal Program Complexity Model and Its
– Tian, Zelkowitz
- 1992
|
|
4
|
Simple Proofs of Lower Bounds for Polynomial Evaluation in "Complexity of Computer Computations
– Reingold, Stocks
- 1972
|
|
4
|
Understanding and Using Program Complexity to Improve Software Development
– Tian
- 1992
|
|
2
|
New Directions in Testing in "Distributed Computing and Cryptography
– Lipton
- 1991
|
|
2
|
U-Processes: Rates of Convergence, The Ann. of Statist. 15(2):780--799
– Nolan, Pollard
- 1987
|
|
1
|
Elements of Software Science," Elsevier-North
– Halstead
- 1977
|
